GATE DA - 2026 (Live + Recorded)

In this course, you will gain access to our currently ongoing classes, and starting from January 2025, we will begin live classes for all subjects. If you are preparing for GATE 2026, this course is ideal for you. The course validity until February 28, 2026.

The GATE (Graduate Aptitude Test in Engineering) Data Science and Artificial Intelligence course covers a comprehensive range of subjects that are crucial for understanding and excelling in the field. The syllabus is designed to assess candidates' knowledge in various areas related to data science, artificial intelligence, and related fields.

Once the LIVE session is done, the same video will be available in the recorded format within 1 hour.

Key Features:

1. 300+ Hours of Content.
2. GATE 2025 Videos Access. 
3. Practice Questions.
4. Test Series. (Test Series will be available from June 30th)
5. Doubt Clearing Sessions.

Instructors

Ravindrababu Ravula is a dedicated Teacher with 15+ years of experience and a deep passion for computer science. Students call him RBR Sir and he did his Masters' degree in Computer Science from IISc Bangalore.

Jay Bansal (AIR 2) did his MTech from IIT Bombay (Specialising in deep networks and image processing). Working as an ML Engineer at Google, working on making cool products using state-of-the-art LLMs like Bard and Gemini.

Hari (AIR 6) is a gold medallist from the prestigious Indian Institute of Science (IISc). He has been driven by a fervent passion for AI since his undergraduate days. His dedication to understanding AI's potential impact on society has shaped his career path, leading him to become the tech lead for the Responsible AI team in India for Microsoft Copilot, the cutting-edge innovation that has taken the tech industry by storm.

Venkatesh E completed his MTech in Artificial Intelligence from IIT Hyderabad. He is currently a Machine Learning Engineer at Qualcomm, where he works on the Qualcomm Cloud AI100 compute accelerator, a leading technology for AI workload inferencing. With a deep interest in Natural Language Processing, Venkatesh has published two notable research papers in prestigious conferences, AAAI-21 and ACL-23, underscoring his contributions to the field.

Syllabus

Probability and Statistics
Linear Algebra
Calculus and Optimization
Programming, Data Structures, and Algorithms
Database Management and Warehousing
Machine Learning
Artificial Intelligence
General Aptitude

Projects:

1. Linear Regression for Real Estate Valuation

2. Email Spam Detection using Naive Bayes

3. Customer Churn Prediction with Logistic Regression

4. K-Nearest Neighbors for Handwritten Digit Classification

5. Decision Trees for Loan Approval Prediction

6. Support Vector Machines for Breast Cancer Diagnosis

7. Market Basket Analysis with Association Rules

8. Clustering News Articles with K-Means

9. Dimensionality Reduction with PCA on Iris Dataset

10. AI Tic-Tac-Toe Game with Minimax Algorithm

11. Ridge Regression for Bias-Variance Trade-Off Analysis

12. Feed-forward neural Network for Image Classification

13. Hierarchical Clustering for Gene Expression Data Analysis

14. Logistic Regression with Cross-Validation for Credit Scoring

15. Predicting Stock Prices using Time Series Analysis and LSTM Networks

16. Natural Language Processing for Sentiment Analysis

17. Adversarial Search in Connect Four Game

18. Facial Recognition with Support Vector Machines

 

 

For Any Queries:

Email: gate2014.ravindra@gmail.com

Contact Number: 9490731198 (10 AM - 6 PM)

 

 

Note: No Refund